class_docstr: Abstract agent class that can interact with a batch of envs.
docstr: Observe a batch of action consequences.
  
  Args:
      batch_obs (Sequence of ~object): Observations.
      batch_reward (Sequence of float): Rewards.
      batch_done (Sequence of boolean): Boolean values where True
          indicates the current state is terminal.
      batch_reset (Sequence of boolean): Boolean values where True
          indicates the current episode will be reset, even if the
          current state is not terminal.
  
  Returns:
      None
docstr_tok: ["Observe","a","batch","of","action","consequences",".","Args",":","batch_obs","(","Sequence","of","~object",")",":","Observations",".","batch_reward","(","Sequence","of","float",")",":","Rewards",".","batch_done","(","Sequence","of","boolean",")",":","Boolean","values","where","True","indicates","the","current","state","is","terminal",".","batch_reset","(","Sequence","of","boolean",")",":","Boolean","values","where","True","indicates","the","current","episode","will","be","reset",",","even","if","the","current","state","is","not","terminal",".","Returns",":","None"]
code: def batch_observe(
      self,
      batch_obs: Sequence[Any],
      batch_reward: Sequence[float],
      batch_done: Sequence[bool],
      batch_reset: Sequence[bool],
  ) -> None:
      """Observe a batch of action consequences.
  
      Args:
          batch_obs (Sequence of ~object): Observations.
          batch_reward (Sequence of float): Rewards.
          batch_done (Sequence of boolean): Boolean values where True
              indicates the current state is terminal.
          batch_reset (Sequence of boolean): Boolean values where True
              indicates the current episode will be reset, even if the
              current state is not terminal.
  
      Returns:
          None
      """
      raise NotImplementedError()
  
imports: import contextlib
  import os
  from abc import ABCMeta, abstractmethod, abstractproperty
  from typing import Any, List, Optional, Sequence, Tuple
  import torch
label_desc: Use image node_id 4 for calling the BatchAgent obj's underlying member method code with example usage: obj.batch_observe(batch_obs, batch_reward, batch_done, batch_reset) without return types